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Smooth Transition Autoregressive-GARCH Model in Forecasting Non-linear Economic Time Series Data

Author

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  • Akintunde Mutairu Oyewale
  • Shangodoyin Dahud Kehinde
  • Kgosi Phazamile

Abstract

The regime switching models are particularly popular in the comity of non-linear models; it is of interest to investigate regime switching models with GARCH specification. GARCH model was augmented with STAR model vis-a vis Exponential autoregressive GARCH (EAR-GARCH), Exponential smooth transition autoregressive GARCH (ESTAR- GARCH) model and Logistic smooth transition autoregressive GARCH (LSTAR-GARCH) model. The properties of the new models were derived and compared with conventional GARCH model which shows that the variance obtained for STAR-GARCH model was minimum compared to classical GARCH model, the new methodology proposed is illustrated with foreign exchange rate data from Great Britain (Pound) and Botswana (Pula) against United States of America (Dollar). It is evident that all STAR-GARCH outperformed the classical GARCH model, however, LSTAR-GARCH performed best and closely followed by ESTAR-GARCH, this is followed by EAR-GARCH. The implication is that the use of LSTAR –GARCH produces the best result; however LSTAR may be utilized in some occasions.

Suggested Citation

  • Akintunde Mutairu Oyewale & Shangodoyin Dahud Kehinde & Kgosi Phazamile, 2013. "Smooth Transition Autoregressive-GARCH Model in Forecasting Non-linear Economic Time Series Data," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 2(2), pages 1-2.
  • Handle: RePEc:spt:stecon:v:2:y:2013:i:2:f:2_2_2
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    Cited by:

    1. Melike Bildirici & Işıl Şahin Onat & Özgür Ömer Ersin, 2023. "Forecasting BDI Sea Freight Shipment Cost, VIX Investor Sentiment and MSCI Global Stock Market Indicator Indices: LSTAR-GARCH and LSTAR-APGARCH Models," Mathematics, MDPI, vol. 11(5), pages 1-27, March.

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